An Embedded Acquisition System for Remote Monitoring of Tire Status in F1 Race Cars through Thermal Images G. Danese, M. Giachero, F. Leporati, N. Nazzicari, M. Nobis Department of Computer Engineering and Systems Science University of Pavia, via Ferrata 1, 27100 Pavia, Italy
[email protected]
As the acquisition frame rate increases, the compression frame rate increases until the CPU usage reaches its maximum. At this point, the compression frame rate enters in a critical region where it begins to decline rapidly. Compression rate (fps)
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Motivation One of the most critical performance factors for any race car is tires management. In particular, the main factor which provides information about the tires workload is the temperature. Up until now, the race engineers’ knowledge of how the tires performed has traditionally been limited to temperature readings, manually taken when the car returns to the pits. It does not provide the engineer with any real idea about how the tires are working at a specific part of the track on any specific lap. Having a better knowledge about how the tires work could offer an important advantage allowing to get to extremely pointy setups. To optimize tires usage, a more accurate way of monitoring their temperatures is presented.
The goal is to maintain an optimal compression frame rate acting on a variable directly related to it: the number of frames in the encoder input buffer. The behavior of the buffer, in fact, can be assimilated to an integrator, where the input variable is the acquisition frame rate and the output is the number of queued frames. We analyzed different control techniques to achieve the correct frame rate allowing an optimal compression. The best results are reached with a second order sliding mode method called “super twisting”. It is defined “second order” because the control law (needed to ensure a robust regulation to zero) doesn’t act on the system input but on its derivative. By comparing the results with those obtained with a “first order” sliding mode, one can see the state remaining close to the desired value with a much higher precision. state
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Thermal camera modeling The internal camera model isn’t available to end users, who only get a 160x128x8 greyscale image. Moreover, modern cameras have a lot of automatic image adjustments (brightness, contrast, etc.) that modify the original data to give end (human) user a better image. All those mechanisms modify original data and need to be switched off if you want to perform data analysis To identify the connection between pixel brightness and measured temperature we provided different temperature input values and acquired the relative color We restricted the analysis to the 50150 °C (120300 °F) range, which is the typical tire temperature range. Fitting samples using a linear and a quadratic model led to the interpolations shown in the figures below.
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Processor: Freescale e300 PowerPC on MPC8349E MDS development board Operating system: Busybox/Linux with freescalepatched kernel 2.6.11 Camera image format: YUV444 Two compressed format: JPEG2000 (using JASPER) and MPEG4 (using XVID4) Two cameras ● Prosilica GE680C (visible spectrum), and ● FLIR Micron A10 (infrared)
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Since both models passed the χ2 test and showed good adaptation to the experimental data, we chose to use the simpler linear model.
Awards This work has been chosen as one of the finalists for the Altran Engineering Academy, a technical widespectrum competition focusing on innovative automotive ideas sponsored by Renault.
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We present a new approach to study the tire temperature on a F1 race car using infrared cameras to effectively monitor its evolution. Thanks to this technique it is possible to acquire thermal images and send them to the pits to have a direct knowledge of tire usage. Before the transmission, the images need to be compressed to avoid the saturation of the limited telemetric bandwidth (100 KB/s). The realtime transmission of the images to the pits is crucial for the effectiveness of the entire system. This issue has been dealt with particular control techniques properly managing the frame compression rate.
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Abstract
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